Field of the Invention
This invention relates generally to monitoring systems, and more particularly to personal monitoring systems that are used to track a person's movements for detecting if the person has fallen and may have been injured.
Description of Related Art
Various care systems exist for monitoring a person's movements. Some systems monitor the movements of the elderly and persons with medical conditions; and such monitoring allows for timely interventions by those who are responsible for diagnosing, caring, rescuing, treating, or otherwise assisting such individuals. There are also many systems for monitoring young and uninjured persons, for tracking daily habits, activity levels, and similar data (e.g., steps taken during the day, calories burned, hours of sleep, etc.). Examples of prior art systems are as follows:
Devaul, U.S. 2006/0282021, teaches a motion analysis telemonitor system that includes a wearable monitoring device that monitors the activity level and movements of a person wearing the device. The wearable monitoring device is used to track fire-fighters, and is able to determine whether the person has fallen through a model analysis technique using characteristic movements of a fall. The wearable device generally transmits data and alerts over a short distance to a console. The console, in turn, transmits data and alerts to a monitoring center. The motion analysis telemonitor system is also able to monitor progression of a disease through changes in movement, which can indicate fatigue.
Devaul teaches the use of “Bayes Theorem” to assist in determining classification of any movement into a model, to assist in determining whether a movement is a fall (or similar situation) or regular movement. This system also includes ancillary components, such as a GPS system, a dead reckoning system, and other components, and may be used in conjunction with a cell phone or similar electronics device.
Jacobsen, U.S. Pat. No. 6,160,478, teaches a health monitoring system for monitoring the elderly which uses wristbands having accelerometers. The system alerts caregivers in the event of a fall. While Jacobson does not teach the use of artificial intelligence, it instead looks for “spikes” in movement that may indicate a fall, especially if followed by a period of the person remaining prone and/or not moving.
Carlton-Foss, U.S. Pat. No. 8,217,795, teaches a fall detection system that includes a wearable monitoring device that monitors the movement of a person, and may be worn on the wrist or other suitable location. The device monitors a sensor (e.g., accelerometer) and detects variation from the normal range and duration thereof. The system determines whether the wearer has fallen through an algorithmic analysis technique using parameters to evaluate the accelerations and timings of the events that comprise a fall. If the combination of the timing and variations from the normal ranges are sufficient as compared to preset thresholds, a fall report will be generated. The wearable device optionally allows qualified professionals to adjust or customize the parameters to optimize the evaluation to the requirements of particular users or classes of users. The wearable device generally transmits data and alerts over a short distance to a console or over a long distance using a connection to a long-distance back haul communication system such as cell network or internet or both. The device thus transmits data and alerts to a call center or other designated location.
Zhang, U.S. Pat. No. 8,952,818, teaches a wearable fall detection device configured for monitoring a wearer of the device. The device comprises a first sensor configured to generate elevation data that represents an elevation of the device, and a second sensor configured to generate acceleration data that represents a magnitude of acceleration of the device. The device also includes a processor configured to determine, based on the elevation data, an elevation of a floor located underneath the wearer, and detect a fall affecting the wearer. Detecting a fall may be done by determining that the acceleration data satisfies a fall hypothesis condition, and determining, based on the elevation data, that the apparatus is vertically displaced from the floor by less than a threshold distance.
Doezema, U.S. 2013/0135097, teaches a wearable, hands-free emergency alert device that responds automatically to a measurable physical effect of a fall event by the wearer to send an alert signal to a remote responder. The wearable device may be a bracelet with a flex circuit including an accelerometer; a manual alert to signal non-fall emergencies; a microphone and/or audio chip for voice communications between the user of the wearable device and a remote responder; one or more charging contacts so as to allow for induction and/or wireless charging of the device; and a wireless transmitter capable of sending a wireless alert signal in response to a sensed fall and capable of generating a response signal in response to receipt of a ping signal which may be used to determine the device's location.
Luo, W.O. 2010108287, teaches a wearable intelligent healthcare system for monitoring a subject and providing feedback from physiological sensors, activity sensors, a processor, a real-time detection and analyzing module for continuous health and activity monitoring, adjustable user setting mode with the adaptive optimization, data-collecting capability to record important health information, audio outputs to the user through audio path and audio interface, preset and user confirmable alarm conditions via wireless communications network to the appropriate individual for prompt and necessary assistance. The system uses noninvasive monitoring technology for continuous, painless and bloodless health state monitoring. The system works through the short range wireless link with carry-on mobile unit for displaying health information, making urgent contact to support center, doctor or individual, and for information transmission with a healthcare center.
While the prior art teaches various related systems and method, the prior art fails to teach a system and method with the novel and non-obvious elements and improvements that are claimed in the present application.